In a free-field situation, a radio propagation model can be used to compute the distance between two radio units from the received signal strength, provided that the transmit power of the transmitting unit is known. When several radio anchors (i.e., radio units with known locations) are present, the received signal strengths can be used to estimate the location of a radio unit by means of trilateration.
Indoor location systems are becoming more and more popular, with a lot of applications such as user navigation, target advertisement, geo-fencing, and the like. However, the accuracy of trilateration approaches is limited due to large ambiguities in the radio propagation model in an environment that cannot be considered as a free field, i.e., any environment containing structures that interact with radio signals and that can cause distortions to the radio signals. A typical non-free-field situation is an interior of a building, wherein walls, floors, furniture and various physical structures interact with radio signals in a complex manner that differs substantially from a free-field situation.
It is however possible to locate a single radio unit relative to a plurality of radio anchors, operating in the radio frequency (RF) domain in a non-free-field environment, by using the signal strengths received between the radio unit and the radio anchors.
A typical indoor location system may comprise at least three components. Firstly, there are one or more target mobile devices to locate, called mobile nodes. The second component is a group of reference points of known locations, called anchor nodes. The third component is a computing entity, called location engine, to compute the relative locations of the mobiles nodes in relation to the anchor nodes.
In practice, the performance of the zone-based approach, as described for example in the WO2014/083494A2, is dependent on the number of anchor nodes per zone. The more anchors in each zone, the better the zoning result that can be achieved. However, given a density of anchor nodes such as the luminaires of a lighting network in an indoor environment, the size of each zone in turn gets larger. As a consequence, the resolution of the location result is compromised due to the enlarged size of each zone. This side effect is highly undesirable since it is the aim of any typical indoor location system to achieve location results with high resolution.
To obtain reliable indoor location performance for the zone-based approach with a higher accuracy resolution, it is desirable to increase the spatial density of anchor nodes, resulting in additional system cost and complexity.